Thus, the conclusion is that when you have uncertainty in your predictive system, you actually change your cost function while you’re learning a new internal model. I find this really interesting because it’s a good piece of evidence that uncertainty in the predictive system feeds into the selection of a new cost function for a movement, rather than the motor system just sticking with the old cost function and continuing to bash away.